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ferc-elibrary-mcp

FERC eLibrary MCP

Сервер Model Context Protocol и асинхронная библиотека на Python для поиска по публичной eLibrary FERC, просмотра листов досье и загрузки публичных документов. Работает с любым MCP-клиентом (Claude Desktop, Cursor, Claude Code и другими).

Дисклеймер

FERC не публикует официальный API для разработчиков eLibrary. Этот проект обращается к тому же недокументированному JSON-бэкенду, который использует публичный сайт (https://elibrary.ferc.gov/eLibrarywebapi/api/). Этот интерфейс может меняться без предупреждения.

  • Только публичные документы — без логина FERC, CEII, привилегированных или защищённых материалов.

  • Соблюдайте вежливость в отношении лимитов запросов; клиент по умолчанию делает паузы между запросами.

  • Используйте для исследования публично доступных документов, а не как замену официальным процедурам доступа.

Related MCP server: @cyanheads/secedgar-mcp-server

Установка в Claude Desktop (проще всего)

Никакого Python, терминала или JSON. Claude Desktop установит сервер за вас.

  1. Установите Claude Desktop.

  2. Скачайте ferc-elibrary.mcpb из последнего релиза на GitHub.

  3. Дважды щёлкните по файлу или перетащите его в Claude Desktop → Settings → Extensions.

  4. Нажмите Install. Оставьте папку загрузки как есть, если не хотите сохранять PDF в другом месте.

  5. Спросите Claude обычным языком, например:

    • Search eLibrary for comments and protests about the Ashokan pumped storage project in the last year.

    • Pull the docket sheet for CP21-470 and list related filings.

    • Download the public PDF for accession 20201119-5202.

Первый запуск может занять минуту, пока Claude устанавливает Python через uv. После этого он запускается быстро. Скачанные файлы сохраняются в Downloads/ferc-elibrary (или в выбранную вами папку). Только публичные документы.

Если релиза ещё нет, сопровождающий может собрать тот же файл командой:

npx --yes @anthropic-ai/mcpb pack . dist/ferc-elibrary.mcpb

Затем отправить dist/ferc-elibrary.mcpb по email или через AirDrop.

Требования

  • Расширение Claude Desktop: ничего не нужно на вашей машине (Claude управляет Python через uv)

  • uvx / библиотека / контрибьюторы: Python 3.12+ и uv

Установка

Конечные пользователи (другие MCP-клиенты)

Клонирование не требуется. Клиенты запускают сервер через uvx из git (см. конфигурацию MCP-клиента). Замените OWNER на владельца репозитория на GitHub после публикации:

uvx --from git+https://github.com/OWNER/ferc-elibrary-mcp ferc-elibrary-mcp

Контрибьюторы

git clone https://github.com/OWNER/ferc-elibrary-mcp
cd ferc-elibrary-mcp
uv sync

Использование библиотеки

ELibraryClient — это асинхронный контекстный менеджер. Используйте его в своём коде без запуска MCP-сервера:

import asyncio
from ferc_elibrary_mcp import ELibraryClient


async def main() -> None:
    async with ELibraryClient() as client:
        raw, summaries, dates = await client.search(
            query="shared facilities agreement",
            match="phrase",
        )
        print(raw.total_hits, dates.source, len(summaries))
        if summaries:
            filing = await client.get_filing(summaries[0].accession_number)
            print(filing.description, filing.url)


asyncio.run(main())

Загрузки сохраняются в FERC_DOWNLOAD_DIR (по умолчанию ~/Downloads/ferc-elibrary). Необязательно: задайте FERC_RATE_LIMIT_SECONDS (по умолчанию 0.5).

Инструменты

Инструмент

Назначение

search_filings

Поиск по ключевым словам, номеру досье, номеру доступа (accession), типу документа, категории и отрасли. Только публичные документы. См. Фильтрация по дате о том, как выбирается окно дат.

get_docket

Лист досье: связанные документы, заявители, номера доступа. См. Листы досье и поиск о том, чем отличается от search_filings.

get_filing

Метаданные одного документа по номеру доступа (YYYYMMDD-NNNN).

list_files

Файлы, прикреплённые к номеру доступа (вызывать перед загрузкой).

get_filing_text

Скачать одно публичное вложение и вернуть извлечённый обычный текст (PDF/DOCX/text). Используйте для чтения или резюмирования документов — download_file только сохраняет локальный путь.

download_file

Сохранить публичный одиночный файл, zip-архив по одному номеру доступа или сгенерированный PDF в FERC_DOWNLOAD_DIR. Не возвращает байты.

download_bundle

Предпочтительно для массовой загрузки: Zip & Download многих публичных файлов из разных номеров доступа одним запросом в FERC_DOWNLOAD_DIR/bundles, с папками по каждому номеру доступа.

collect_related

Поиск по термину или типу документа, затем группировка связанных документов по досье (не более 10 досье × 50 документов). Необязательный download использует download_bundle (до 10 файлов).

Привилегированные, защищённые документы и CEII отклоняются.

Фильтрация по дате

Значения дат по умолчанию зависят от контекста, потому что 60-дневное окно, наложенное на именованное досье, молча скрывает большую часть разбирательства:

Вызов

Применяемое окно

date_range_source

docket= или accession_number=

нет, всё разбирательство

none

открытый запрос без дат

последние 60 дней

default_60_day

любые явные start_date/end_date

как указано

explicit

Каждый инструмент, принимающий даты — search_filings, collect_related и get_docket, — сообщает date_range_applied, date_range_source, date_field_applied, results_may_be_date_limited и date_field_filtered_client_side, в том числе при пустых результатах, поскольку пустой набор под незамеченным значением по умолчанию — это случай, который чаще всего вводит в заблуждение. Считайте total_hits полным количеством только когда results_may_be_date_limited равно false.

Все три инструмента определяют своё окно через единый хелпер resolve_date_range и сообщают его через DateRangeResolution.as_envelope(). Реестровый тест обходит список инструментов и завершается ошибкой, если любой инструмент, принимающий start_date, не содержит конверт или параметр date_field, так что новый инструмент поискового типа оказывается покрыт в день его добавления.

date_field выбирает, по какой дате фильтрует диапазон: filed (по умолчанию) или issued. Используйте issued для расчёта сроков: повторное слушание по FPA 313(a) и большинство сроков Комиссии для комментариев и соблюдения требований отсчитываются от даты вынесения решения, и эти две даты расходятся. По делу ER26-3176 документ с номером доступа 20260807-5037 подан 08/07, но вынесен 08/06, поэтому поиск по дате подачи за 08/06 его пропускает. Обе даты фильтруются на стороне сервера eLibrary, поэтому пагинация остаётся точной.

Листы досье и поиск

get_docket и search_filings охватывают одни и те же документы, но добираются до них по-разному, и различия сообщаются, а не оставляются для самостоятельного обнаружения:

  • Одна строка на документ. eLibrary возвращает одну строку на каждую привязку к досье, поэтому ходатайство, адресованное делам -000, -001 и -002, приходит трижды, и его totalHits считает его три раза. Строки объединяются по номеру доступа, каждая привязка сохраняется в docket_numbers, а count_basis сообщает distinct_accession. По делу EL25-49 это разница между заявленными FERC 380 и 312 документами, которые реально можно получить.

  • Пагинация на стороне клиента. numHits и pageNumber не разрезают лист надёжно — строк на странице больше запрошенного лимита, а более поздние страницы перекрываются, — поэтому лист получается один раз и разбивается на страницы локально. page начинается с 1 в обоих инструментах; page=0 принимается как страница 1.

  • Доступность. Лист не содержит кода доступности, поэтому get_docket не может фильтровать по нему и сообщает availability_scope: "all". search_filings по умолчанию работает только с публичными документами. Поэтому лист досье может содержать несколько привилегированных документов, которые поиск пропускает; по делу EL25-49 это 3 из 312.

  • Порядок. get_docket возвращает от старых к новым (хронологически, как лист досье), search_filings — от новых к старым. Передайте sort_order="newest_first", чтобы выровнять их.

  • Даты вынесения. Лист сообщает каждую issued_date как нулевой маркер .NET 0001-01-01, поэтому она отображается как пустая строка, а не как дата первого года. date_field="issued" у get_docket определяет окно через поисковый endpoint, который содержит реальные даты вынесения, и устанавливает date_field_filtered_client_side: true.

Опечатанные копии

get_filing и list_files сообщают has_nonpublic_counterpart — признак того, что на том же номере доступа, вероятно, существует опечатанная, защищённая версия или версия CEII — то, для доступа к чему вы ходатайствовали бы по 18 C.F.R. 388.113. Признак выводится из соглашения об именовании файлов (имя файла или описание с префиксом PUBLIC или содержащее REDACTED), поэтому nonpublic_counterpart_basis сообщает file_naming_convention, чтобы пометить признак как эвристический, а не авторитетный. Названия коммунальных предприятий, такие как «Public Service Company», исключаются во избежание ложных срабатываний. Защищённый контент никогда не возвращается, и этот признак намеренно отсутствует в результатах search_filings.

Точность поиска

eLibrary трактует голый многословный запрос как независимые термины, что погребает документы, реально содержащие фразу. Два параметра управляют этим:

  • match: phrase (по умолчанию) требует точную фразу, all требует каждый термин, any — это свободное сопоставление терминов FERC.

  • search_in: both (по умолчанию) ищет по описаниям и полному тексту документа, description — только по заголовку документа, full_text — только по телу документа.

Поиск shared facilities agreement по документам 2026 года:

match

search_in

Найдено

any

both

5 627

phrase

both

324

phrase

description

65

Используйте search_in="description", если фразовый поиск всё ещё даёт слишком много шума; поиск по полному тексту находит любое мимолётное упоминание глубоко внутри вложения. Синтаксис eLibrary, который вы пишете сами (кавычки, AND, OR, NOT, NEAR), передаётся без изменений.

Форматы загрузки

download_file принимает format для одного номера доступа:

  • native (по умолчанию) сохраняет один файл, указанный через file_id.

  • zip упаковывает все файлы этого номера доступа.

  • pdf просит eLibrary сгенерировать объединённый PDF номера доступа.

Для многих файлов или многих номеров доступа используйте download_bundle. Он вызывает тот же endpoint Zip & Download, который использует интерфейс eLibrary, когда вы заполняете зелёную папку-молнию, — один HTTP-запрос со списком идентификаторов файлов, а не N× (get_filing + загрузка + ожидание из-за лимита запросов). Передайте любую смесь accession_numbers, file_ids и/или docket. По умолчанию плоские имена FERC (20260716-5098_Agreement.pdf) переписываются в папки (20260716-5098/Agreement.pdf). Лимиты по умолчанию: 100 файлов / 500 МБ (FERC_MAX_BUNDLE_FILES, FERC_MAX_BUNDLE_BYTES); увеличьте FERC_BUNDLE_TIMEOUT_SECONDS (по умолчанию 300) для очень больших архивов.

collect_related(..., download=True) использует этот массовый путь и возвращает поле bundle, указывающее на архив.

eLibrary помечает каждую загрузку как application/octet-stream, поэтому реальный тип определяется по магическим байтам и расширению файла (расширения OOXML имеют приоритет над ZIP-магией, поскольку .docx сам по себе является ZIP). Результаты одиночных файлов также сообщают expected_size из метаданных FERC рядом с реально записанными байтами, а также size_matches_metadata и is_bundle, так что получение архива, когда вы просили один файл, видно, а не происходит молча. format=zip для номера доступа с одним файлом разворачивается в этот файл и обновляет эти поля в соответствии с сохранённым.

Сборка пакета для Claude Desktop

Из клона, при наличии Node.js 18+:

npx --yes @anthropic-ai/mcpb validate manifest.json
npx --yes @anthropic-ai/mcpb pack . dist/ferc-elibrary.mcpb

Пакет использует server.type = "uv": он содержит исходный код и pyproject.toml, а не вендоренное виртуальное окружение. Claude Desktop загружает Python и зависимости при первом запуске. CI собирает тот же файл при каждом пуше и прикрепляет его к релизам на GitHub.

Конфигурация MCP-клиента

Пользователям Claude Desktop следует предпочесть установку .mcpb в один клик. JSON ниже — для Cursor, Claude Code и других клиентов.

Замените OWNER на владельца репозитория на GitHub. Все фрагменты используют переносимый uvx из git — без абсолютных путей на машине.

Загрузки по умолчанию сохраняются в ~/Downloads/ferc-elibrary, если FERC_DOWNLOAD_DIR не задан. Установите FERC_MCP_IDLE_TIMEOUT_SECONDS, чтобы завершать осиротевшие экземпляры stdio (см. Осиротевшие серверные процессы); не задавайте его или используйте 0, чтобы никогда не завершаться самостоятельно (по умолчанию).

Claude Desktop

Добавьте в ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) или в эквивалентный конфигурационный файл Claude Desktop в вашей ОС:

{
  "mcpServers": {
    "ferc-elibrary": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/OWNER/ferc-elibrary-mcp",
        "ferc-elibrary-mcp"
      ],
      "env": {
        "FERC_DOWNLOAD_DIR": "/Users/YOU/Downloads/ferc-elibrary",
        "FERC_MCP_IDLE_TIMEOUT_SECONDS": "14400"
      }
    }
  }
}

Используйте абсолютный путь для FERC_DOWNLOAD_DIR (раскройте ~ самостоятельно). Claude Desktop — это графическое приложение, которое может не раскрывать ~ и не наследовать PATH вашей оболочки; убедитесь, что uvx находится в PATH, доступном приложению (например, установите uv в масштабе всей системы или укажите полный путь к uvx).

Полностью завершите работу Claude Desktop и откройте его заново. Убедитесь, что сервер отображается в разделе Settings → Developer.

Cursor

Добавьте в .cursor/mcp.json в проекте либо в пользовательскую конфигурацию MCP:

{
  "mcpServers": {
    "ferc-elibrary": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/OWNER/ferc-elibrary-mcp",
        "ferc-elibrary-mcp"
      ],
      "env": {
        "FERC_DOWNLOAD_DIR": "/Users/YOU/Downloads/ferc-elibrary",
        "FERC_MCP_IDLE_TIMEOUT_SECONDS": "14400"
      }
    }
  }
}

Claude Code

В рамках проекта (.mcp.json в корне проекта) или на уровне пользователя (claude mcp add / ~/.claude.json):

{
  "mcpServers": {
    "ferc-elibrary": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/OWNER/ferc-elibrary-mcp",
        "ferc-elibrary-mcp"
      ],
      "env": {
        "FERC_DOWNLOAD_DIR": "${HOME}/Downloads/ferc-elibrary",
        "FERC_MCP_IDLE_TIMEOUT_SECONDS": "14400"
      }
    }
  }
}

Или через CLI:

claude mcp add --scope user ferc-elibrary -- \
  uvx --from git+https://github.com/OWNER/ferc-elibrary-mcp ferc-elibrary-mcp

Примеры запросов

  • Выполните в eLibrary поиск комментариев и возражений по проекту гидроаккумулирующей станции Ашокан за последний год.

  • Получите реестр дела CP21-470 и перечислите связанные документы.

  • Найдите выпуски Order/Opinion в электроэнергетике за январь 2024 года и соберите связанные документы по делам.

  • Скачайте публичный PDF для регистрационного номера 20201119-5202.

Тестирование с MCP Inspector

Из клона проекта:

npx @modelcontextprotocol/inspector uv run ferc-elibrary-mcp

Вызовите search_filings с параметром docket P-15056-000 и start_date / end_date около 2020-11-19, чтобы подтвердить известный публичный результат.

Тесты

uv run pytest
uv run pytest -m live   # optional smoke test against the live public API

Ограничения

  • Только публичные документы. Никаких файлов, требующих входа в FERC, а также CEII, привилегированных или защищённых файлов.

  • Байты файлов записываются на диск, а не возвращаются в ответе инструмента MCP.

  • collect_related ограничивает количество дел и файлов, которые он будет получать, чтобы широкий запрос не мог выгрузить тысячи документов в контекст.

  • Бэкенд не документирован и находится за прокси, который время от времени возвращает 502/503/520. Временные ответы 5xx повторяются до трёх раз с возрастающей задержкой.

  • Для некоторых некорректно сформированных тел запросов FERC возвращает HTTP 200 с success: false и строкой исключения .NET. Они порождают ошибку, а не молча возвращают ноль результатов.

Осиротевшие серверные процессы

Некоторые MCP-клиенты (в частности, Claude Desktop) иногда запускают два stdio-сервера с интервалом менее секунды и взаимодействуют только с одним из них. Они могут не закрывать stdin у заброшенного экземпляра, поэтому тот процесс никогда не видит EOF и простаивает вечно — на практике это одна утёкшая пара процессов в день, а вызовы инструментов, направленные на зависший экземпляр, зависают до истечения собственного таймаута клиента, а не завершаются ошибкой.

Сам сервер не виноват: он корректно завершает работу при EOF на stdin (код возврата 0) и по SIGTERM. У заброшенного экземпляра просто нет способа заметить, что его никто не слушает.

Установите FERC_MCP_IDLE_TIMEOUT_SECONDS, чтобы экземпляр, который не получал сообщений в течение этого времени, завершал себя сам через SIGTERM. Любой запрос сбрасывает таймер, поэтому используемый сервер не затрагивается; завершается только полностью заброшенный. По умолчанию эта возможность отключена (0), поскольку здоровый, но неиспользуемый сервер тоже завершился бы, и тогда восстановление зависит от того, перезапустит ли его клиент. Примеры конфигураций выше задают 4 часа — это с запасом больше любого перерыва в активной сессии.

Чтобы вручную найти и удалить осиротевшие процессы:

ps -eo pid,etime,command | grep '[f]erc-elibrary-mcp'
kill -TERM <pid>   # they are idle, not wedged; no -9 needed

Лицензия

MIT — см. LICENSE.

Available Tools

13 tools
cache_statusC

Report what the document store holds for a docket or accession.

ParametersJSON Schema
NameRequiredDescriptionDefault
docketNo
accessionNo

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

C2.7/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only inspection via 'Report', but does not state whether it mutates anything, whether both parameters may be supplied together, what happens when both are null, or what 'holds' concretely means (e.g., existence, metadata, document segments).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no filler, and the core idea is front-loaded. It is efficient, though brevity comes at the cost of missing operational context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Although an output schema exists so return-value details need not be in the description, the tool is underspecified for a user trying to call it correctly. Key invocation constraints—parameter optionality, exclusivity, and what a cache status report actually contains—are absent, making this incomplete for reliable tool selection and use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for the bare schema. It adds only the relationship 'docket or accession', but does not explain the expected identifier formats, whether at least one is required, whether they are exclusive, or what each parameter affects in the report.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies a specific action ('Report') and a specific resource ('what the document store holds for a docket or accession'), which distinguishes it as a cache-status inspection tool among siblings like get_docket and sync_docket. It does not explicitly name a sibling alternative, but the purpose is not tautological or vague.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no explicit guidance on when to use this tool versus alternatives such as get_docket, sync_docket, or list_files. The intended use case (checking cached holdings before fetching or syncing) is only weakly implied, not stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

download_bundleA

Zip many public files into one archive under FERC_DOWNLOAD_DIR/bundles.

Prefer this over repeated download_file calls. eLibrary's Zip & Download accepts many file IDs in a single request (including across accessions), so one call replaces N metadata lookups + N downloads + N rate-limit waits.

Provide any combination of accession_numbers (all public files on each), file_ids (exact attachments), and/or docket (public files found via search on that docket). Default organize_by_accession=true rewrites FERC's flat accession_filename members into accession/filename folders.

Caps: 100 files and 500 MB by default (FERC_MAX_BUNDLE_FILES / FERC_MAX_BUNDLE_BYTES). Privileged, protected, and CEII accessions — and accessions absent from public search — are skipped and listed in skipped_accessions with a reason and category (restricted vs not_found). Does not return file bytes.

ParametersJSON Schema
NameRequiredDescriptionDefault
docketNo
file_idsNo
accession_numbersNo
organize_by_accessionNo

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full behavioral burden, and it does so thoroughly: it discloses filesystem side effects (writing under FERC_DOWNLOAD_DIR/bundles), default folder reorganization, file/size caps, the skipping behavior for restricted/not-found accessions with reasons and categories, and the fact that it does not return file bytes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but every sentence adds value: purpose, alternative comparison, parameter semantics, caps, skip behavior, and the no-bytes return caveat. It is front-loaded with the core purpose before diving into details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given four optional parameters, no annotations, and no schema descriptions, the description covers all necessary operational context: selection semantics, side effects, limits, failure handling, and return caveats. The presence of an output schema means return-field detail is not required in the description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, but the description compensates by explaining each parameter: accession_numbers select all public files on each accession, file_ids target exact attachments, docket selects public files via search, and organize_by_accession controls folder structure with a clear default behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Zip many public files into one archive under FERC_DOWNLOAD_DIR/bundles.' It also explicitly differentiates itself from the sibling tool download_file by saying 'Prefer this over repeated download_file calls,' making the tool's distinct role unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly states when to use this tool ('Prefer this over repeated download_file calls') and enumerates valid input combinations. It does not explicitly spell out exclusions like 'use download_file for a single file or restricted accessions,' but the restricted/not-found skipping behavior implies those cases are not this tool's purpose.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

download_fileA

Download a public eLibrary file to FERC_DOWNLOAD_DIR.

Does not return file bytes. Privileged, protected, and CEII documents are refused. Call list_files first to pick a file_id.

format=native saves that one original file and is the default. format=zip asks eLibrary for every file on the accession as one archive; if the accession has a single attachment, the archive is unwrapped to that file and content_type / is_bundle / expected_size describe the saved document. format=pdf asks eLibrary to generate a combined PDF of the whole accession.

The result reports expected_size from FERC's metadata alongside the byte count actually written, plus size_matches_metadata and is_bundle, so a mismatch between the file you asked for and the artifact you got is visible.

ParametersJSON Schema
NameRequiredDescriptionDefault
formatNonative
file_idNo
accession_numberYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description fully carries the burden and does so admirably. It discloses the side effect of saving to FERC_DOWNLOAD_DIR, states that file bytes are not returned, explains refused document types, and reveals how format choices change the saved artifact and result metadata.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is detailed yet tightly organized, with each paragraph serving a distinct purpose: primary action, key caveats, format semantics, and result interpretation. No sentence feels redundant or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity, the description covers prerequisites, refusals, format variants, side effects, return-value semantics, and mismatch detection. The presence of an output schema reduces the need to describe return fields, yet the description still adds useful interpretive context about size_matches_metadata and is_bundle.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It thoroughly explains the format enum values, their defaults, and their behavioral differences, and it explains file_id's role via the list_files prerequisite. accession_number is not explicitly explained, though the tool name and context make it reasonably inferable.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Download a public eLibrary file to FERC_DOWNLOAD_DIR.' It clearly distinguishes this tool from siblings by focusing on a single file download and by describing the non-return of file bytes, making its role unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit operational guidance: call list_files first to pick a file_id, and it warns that privileged/protected/CEII documents are refused. It does not explicitly compare against the sibling download_bundle, so the choice between this tool and that alternative is somewhat left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_docketA

Return the docket sheet: related filings, applicants, and accession numbers.

Docket numbers look like CP21-470, ER11-4046, or P-15056-000. Subdockets can be All or a comma-separated list such as 000,001.

page is 1-indexed, matching search_filings. page=0 is accepted as page 1.

One row per filing: eLibrary returns one row per docket association, so a pleading captioned to -000, -001 and -002 arrives three times. Rows are merged on accession number and every association is listed in docket_numbers, so total_hits counts filings you can actually retrieve. count_basis reports distinct_accession to make that explicit.

Scope differs from search_filings in one way worth knowing: the docket sheet carries no availability code, so it cannot filter by availability and reports availability_scope "all". search_filings is public-only by default, so a docket sheet may list a few privileged filings that search omits.

sort_order defaults to oldest_first, the chronological order of a docket sheet. search_filings returns newest first. Pass newest_first to match it.

date_field and the date envelope behave as in search_filings. Since a docket number is always supplied, no 60-day default is ever applied here. An issued-date window is applied to rows after retrieval, reported via date_field_filtered_client_side.

ParametersJSON Schema
NameRequiredDescriptionDefault
pageNo
limitNo
end_dateNo
date_fieldNofiled
sort_orderNooldest_first
start_dateNo
subdocketsNoAll
docket_numberYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does so exceptionally. It discloses row duplication and merging by accession number, total_hits semantics, count_basis=distinct_accession, availability_scope='all', the absence of a 60-day default, client-side date filtering, and page=0 handling. This is far more transparent than most tool descriptions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but every sentence earns its place. It is organized into logical chunks: core purpose, docket/subdocket format, pagination, row-merging behavior, comparison to search_filings, sort order, and date behavior. No fluff or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema exists, the description need not explain return values. It covers edge cases (page=0, subdocket lists, multi-docket filings, privileged filings, client-side date filtering) and differentiates behavior from a key sibling. An agent has enough to call this tool correctly and interpret the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains docket_number format, subdockets values, page indexing, sort_order meaning and default, and date_field/envelope behavior. The only notable omission is the limit parameter, which is left to inference, but the overall parameter guidance is strong.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: 'Return the docket sheet: related filings, applicants, and accession numbers.' It also gives concrete docket number examples and clearly differentiates itself from search_filings by scope and behavior. An agent can confidently identify this tool as the one that retrieves a docket sheet by docket number.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly contrasts get_docket with search_filings: availability handling, sort order defaults, and date-field behavior. It implies the primary use case is when you have a docket number. It does not include an explicit 'use this when / use search_filings when' rule, but the comparisons provide strong routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_document_outlineB

Return PDF bookmarks or a heuristic section map for a stored filing.

ParametersJSON Schema
NameRequiredDescriptionDefault
filenameYes
accession_numberYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

B3.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden of disclosing behavior. It does convey the key fallback behavior: return PDF bookmarks if available, otherwise a heuristic section map. It does not, however, state side effects, error conditions, or whether the operation is read-only, though 'Return' implies non-mutating.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence, front-loaded with the action and output type, and no filler. This is as concise as possible while still conveying the tool's core behavior and fallback.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The presence of an output schema covers return-value details, and the two required parameters are simple strings. Still, the description lacks parameter semantics and usage guidance, so the definition is only minimally complete for an agent choosing among siblings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description needed to explain what accession_number and filename mean, but it does not. The phrase 'stored filing' offers only weak context; the parameter names themselves are doing the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description names a specific verb ('Return') and a precise resource: 'PDF bookmarks or a heuristic section map for a stored filing.' This makes the output clear and distinguishes the tool from siblings like get_filing_text or read_document, which return content rather than a document outline.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description gives no explicit when-to-use advice and does not mention any sibling alternative, so an agent must infer from the tool name and output type when to select it over get_filing_text or search_within_document. There are no exclusion conditions or prerequisites stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_filingA

Fetch metadata for one filing by accession number (YYYYMMDD-NNNN).

has_nonpublic_counterpart signals that a sealed, protected, or CEII version likely exists on the same accession, which is what you would move for access to under 18 C.F.R. 388.113. It is inferred from filer naming convention ("PUBLIC" or "REDACTED" in a file name), so nonpublic_counterpart_basis reports it as file_naming_convention rather than authoritative metadata. No protected content is ever returned.

ParametersJSON Schema
NameRequiredDescriptionDefault
accession_numberYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full disclosure burden. It discloses a meaningful behavioral limitation ('No protected content is ever returned') and explains that has_nonpublic_counterpart is inferred from filer naming conventions rather than authoritative metadata, which is important for interpreting results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, front-loaded with the core purpose, and every sentence adds value: the first states what the tool does, the second explains the nonpublic_counterpart semantics, and the third explicitly reassures about protected content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a single required parameter, an output schema, and one key behavioral caveat, the description is largely complete. It explains the non-authoritative nature of an important field. It could be more complete by explicitly naming get_filing_text as the tool for content, but that is not essential for invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema only declares accession_number as a string with no description, giving 0% schema coverage. The description compensates by providing the exact expected format ('YYYYMMDD-NNNN'), which is crucial for calling the tool correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Fetch'), the resource ('metadata for one filing'), and the key identifier ('accession number (YYYYMMDD-NNNN)'). This distinguishes it from sibling tools like get_filing_text by emphasizing 'metadata' rather than content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for retrieving metadata for a single filing and explicitly notes when a nonpublic counterpart would be relevant (moving for access under 18 C.F.R. 388.113). However, it does not explicitly contrast with search_filings or get_filing_text, leaving some routing decisions to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_filing_textA

Deprecated alias for bounded read_document.

Returns at most max_chars of extracted text and reports total_chars when truncated. Prefer get_document_outline, search_within_document, and read_document for large filings.

ParametersJSON Schema
NameRequiredDescriptionDefault
file_idNo
max_charsNo
accession_numberYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses the truncation behavior ('at most max_chars', 'reports total_chars when truncated') and the deprecated status, which is meaningful behavioral context. It does not mention side effects or permissions, but the read-only nature is clear enough for a deprecated text-retrieval alias.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no wasted words. It front-loads the deprecation and core behavior, then provides routing guidance to alternatives. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The output schema exists, so return-value details are not required. The description covers deprecation, truncation, and alternative tools well, but incomplete parameter semantics for file_id and accession_number prevent full completeness. It is adequate but has clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for parameter meaning. It only explains max_chars; the meanings of accession_number and file_id, and their relationship, are left undocumented. This is a notable gap for an agent trying to call the tool correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is a deprecated alias for read_document and specifies the exact behavior: 'Returns at most max_chars of extracted text.' It names the resource (filing text), the operation (bounded read), and distinguishes itself from siblings by framing it as deprecated and bounded.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly steers agents away from this tool for large filings by recommending get_document_outline, search_within_document, and read_document. However, it does not clearly describe when this tool should still be used, only implies it may be acceptable for smaller bounded reads.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_filesA

List files attached to an accession. Call this before download_file.

See get_filing for what has_nonpublic_counterpart means.

ParametersJSON Schema
NameRequiredDescriptionDefault
accession_numberYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A3.8/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries the burden of behavioral disclosure. It reveals the operation is a listing action and hints at has_nonpublic_counterpart semantics only via cross-reference, but it does not state whether the call is read-only, what metadata is returned, or whether pagination or limits apply.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact: two short sentences with no filler. The first sentence states the action, and the second efficiently redirects to get_filing for a relevant term instead of duplicating context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter listing tool with an output schema available, the description covers the core action and workflow ordering. It is close to sufficient, though it would benefit from a brief note on expected file metadata or read-only behavior since annotations are absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides no description for accession_number (0% coverage), and the description only ties it to 'an accession' and the download workflow. This adds some meaning beyond the bare parameter name, but it does not specify the expected format or how to obtain the accession number.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('List') and a concrete resource ('files attached to an accession'), making the tool's function immediately clear. It also differentiates from download_file by positioning itself as the step before downloading.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says 'Call this before download_file,' which gives clear sequencing guidance. It also points to get_filing for understanding has_nonpublic_counterpart. It does not fully enumerate when not to use other sibling tools, so it stops short of a complete routing guide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

read_documentA

Return bounded plain text from a cached filing attachment.

Never returns the full document unless it fits within max_chars. Responses include total_chars, truncated, and next_char_start / next_page when clipped.

ParametersJSON Schema
NameRequiredDescriptionDefault
pagesNo
char_endNo
filenameYes
max_charsNo
char_startNo
accession_numberYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states the truncation behavior, the guarantee that the full document is never returned unless it fits within max_chars, and the response metadata (total_chars, truncated, next_char_start/next_page) when clipped. This is strong, concrete behavioral detail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tightly scoped sentences with the primary action front-loaded. Every sentence earns its place: the return type and source, the critical size limitation, and the response navigation contract.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The output schema covers return-value details, and the description provides solid behavioral context. However, the 6-parameter schema has zero description coverage and the description compensates only for max_chars, so an agent still lacks sufficient guidance on pagination/range parameters and how this tool compares to siblings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 6 parameters, and the description only adds meaning for max_chars. It does not explain pages, char_start, char_end, accession_number, or filename, leaving key range-selection and document-identification semantics undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Return bounded plain text from a cached filing attachment,' which names a specific verb, resource, and scope. The 'Never returns the full document' constraint clearly differentiates it from sibling tools like get_filing_text, which likely returns complete document text.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The usage context is implied: use this when you need bounded plain text from a cached filing attachment. However, it does not explicitly name alternatives or state when not to use this tool, so the agent must infer routing decisions from sibling names and the bounded-text behavior.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_filingsA

Search public FERC eLibrary filings. Public documents only.

Use for keyword/term search, docket prefix (CP, ER11-4046), accession numbers, or document types such as Order/Opinion, Comments/Protest, or Application/Petition/Request.

Date defaulting: when docket or accession_number is supplied, no date filter is applied and the whole proceeding is searched. For an open-ended query with no dates, the last 60 days is used to keep the result set manageable. Every response reports date_range_applied, date_range_source (explicit/default_60_day/none), and results_may_be_date_limited, so check those before treating total_hits as a complete count.

date_field selects which date start_date and end_date filter on. Use "issued" when computing deadlines: FPA 313(a) rehearing and most Commission-set comment and compliance clocks run from issuance, not from the filed date, and the two differ. Orders are generally best searched by issuance.

match controls how a multi-word query is interpreted. "phrase" (default) requires the exact phrase and is what you want when looking for a named agreement or document. "all" requires every term anywhere. "any" is FERC's loose term matching, which returns high volume and low precision.

search_in controls where the query is matched. "both" (default) covers descriptions and full document text. "description" is far more precise because it matches the filing title rather than any passing mention deep in an attachment. Use it when a phrase search still returns too much noise.

You may also pass eLibrary syntax directly (quotes, AND, OR, NOT, NEAR); it is forwarded unchanged.

ParametersJSON Schema
NameRequiredDescriptionDefault
pageNo
limitNo
matchNophrase
queryNo
docketNo
categoryNo
end_dateNo
industryNo
search_inNoboth
date_fieldNofiled
start_dateNo
document_typeNo
accession_numberNo

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full disclosure burden and meets it well. It reveals the default 60-day window for open-ended queries, the no-date-filter behavior when docket or accession_number is supplied, and the presence of response flags like date_range_applied and results_may_be_date_limited. It also discloses nuanced behaviors around date_field and match modes that an agent would otherwise have to discover by trial.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with a clear opening and topic-focused paragraphs, each sentence adds useful information. The opening repeats 'public' twice ('public FERC eLibrary filings' and 'Public documents only'), which is minor redundancy; otherwise it is appropriately dense for a 13-parameter search tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex search tool with no annotations, this description is unusually complete: it covers search scope, date defaults, parameter behavior, and response caveats. An output schema exists to define the return shape, so the description provides enough context for correct invocation without missing essential operational details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does. It explains docket, accession_number, date_field, match, search_in, and document_type with examples and usage guidance. Only page, limit, category, and industry are not directly addressed, but the most consequential parameters are richly specified.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'Search public FERC eLibrary filings.' It also scopes the tool with 'Public documents only' and lists concrete supported query keys (keywords, docket prefix, accession numbers, document types), making it clearly distinguishable from siblings like get_filing or list_files.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear context on how to search: which fields to use, date defaulting behavior, and trade-offs between match and search_in modes. It stops short of explicitly saying when not to use this tool versus a sibling like get_filing, so it lacks explicit when-not/alternatives guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_within_documentB

Search extracted text for a query and return passages with page/char offsets.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes
filenameYes
max_hitsNo
accession_numberYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

B3.3/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden. It discloses the core read-only search behavior and the output shape, but it does not mention side effects, extraction prerequisites, pagination, max_hits behavior, or edge cases. It is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence with a leading verb and no filler. Every phrase adds meaning: the search action, the input type (extracted text), and the output (passages with offsets).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has four parameters with no schema descriptions and no annotations, so more context is required. The output schema covers the return shape, but the missing parameter semantics and lack of usage guidance leave the description incomplete for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description only clarifies 'query' by referring to it as a query. It does not explain accession_number, filename, or max_hits, leaving the agent to guess why both identifiers are required and how max_hits limits results.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies a specific verb ('Search'), a resource ('extracted text'), and an explicit output ('passages with page/char offsets'). This makes it clear what the tool does and distinguishes it from siblings like get_filing_text and read_document, which return full text rather than matched passages with offsets.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to prefer this tool over alternatives. It does not mention that it is for searching within a single document rather than across filings, and it does not contrast with siblings such as search_filings, get_filing_text, or read_document.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

sync_docketB

Incrementally fetch accessions missing from the document store for a docket.

ParametersJSON Schema
NameRequiredDescriptionDefault
docket_numberYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

B3.2/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It mentions 'incrementally' and the scope 'missing from the document store,' but it does not state whether the tool writes to or mutates the document store, whether it is idempotent, or whether it may be a long-running operation. The wording is ambiguous about side effects, which is a significant gap for a tool named 'sync_docket.'

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence of twelve words, front-loaded with the verb and object. Every word contributes meaning: 'incrementally' clarifies scope, 'missing from the document store' specifies the target set, and 'for a docket' ties it to the parameter. There is no redundant language.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The output schema exists, so return values need not be explained. However, the absence of annotations and the terse description leave important operational context untold: whether the tool mutates the document store, what 'accessions' means in this domain, how 'incrementally' is determined, and whether a prior cache or docket fetch is required. An agent could not fully assess side effects or prerequisites from this description alone.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has one required parameter (docket_number) with zero description coverage. The tool description's 'for a docket' implicitly identifies docket_number as the target docket, adding some contextual meaning. However, it does not specify the expected format, example values, or any constraints, so it only partially compensates for the missing schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('fetch') and a precise resource ('accessions missing from the document store for a docket'). It clearly communicates an incremental sync operation, which is distinct from the other listed tools like get_docket or get_filing. It does not explicitly name sibling alternatives, so it stops short of a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'incrementally fetch accessions missing' implies a backfill/sync scenario, giving some sense of when to use this tool. However, it does not explicitly state when to prefer this tool over alternatives such as get_docket or cache_status, nor does it mention any prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

TDQS

A3.7/5.0
Disambiguation4/5

Most tools target distinct levels of the eLibrary: search, docket metadata, accession metadata, attachment listing, downloads, and document text. The deprecated get_filing_text alias overlaps with read_document and could be confused with get_filing, and collect_related combines search and docket listing, but the descriptions clarify the intended boundaries.

Naming Consistency4/5

Almost every tool follows a verb_noun snake_case pattern such as search_filings, get_docket, and download_file. cache_status breaks the verb pattern, collect_related uses an adjective-like object, and get_filing_text is a stale alias, so the naming is mostly but not fully consistent.

Tool Count4/5

13 tools is within the well-scoped range and covers search, metadata access, file listing, downloads, bundle downloads, document text analysis, and cache management. The deprecated get_filing_text alias and the more internal cache_status/sync_docket tools add slight weight, but the set does not feel bloated.

Completeness5/5

The tools cover the public-filing lifecycle end to end: docket and accession search, metadata retrieval, file listing, single and bundle download, extracted-text reading, within-document search, outlines, and cache synchronization. No obvious operations are missing for the stated FERC eLibrary retrieval domain.

Maintenance

ActivityMaintained
ResponsivenessSyncing

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